# coding: utf-8

IMAGE_DIRECTORY = '/input_dir/datasets/Tiny-ImageNet/'
BATCH_SIZE = 20
NUM_CLASSES = 200
NUM_IMAGES_PER_CLASS = 200
NUM_IMAGES = NUM_CLASSES * NUM_IMAGES_PER_CLASS
TRAINING_IMAGES_DIR = '/input_dir/datasets/Tiny-ImageNet/train/'
TRAIN_SIZE = NUM_IMAGES

NUM_VAL_IMAGES = 4000
VAL_IMAGES_DIR = '/input_dir/datasets/Tiny-ImageNet/val/'
IMAGE_SIZE = 64
NUM_CHANNELS = 3
IMAGE_ARR_SIZE = IMAGE_SIZE * IMAGE_SIZE * NUM_CHANNELS

height = IMAGE_SIZE
width = IMAGE_SIZE
channels = NUM_CHANNELS
n_inputs = height * width * channels
n_outputs = 200
learning_rate = 0.001